In this new season of Adventures in Compliance, host Tom Fox takes a deep dive into the Sherlock Holmes novels. Over this season I will take a deep dive into each novel over a four part series. The four novels we will consider from the ethics and compliance perspective are A Study in Scarlet, The Sign of Four, The Hound of the Baskervilles and The Valley of Fear. We continue our four episode series on the second novel, The Sign of Four by reviewing how Holmes uses data analytics and pattern recognition in this See more +
In this new season of Adventures in Compliance, host Tom Fox takes a deep dive into the Sherlock Holmes novels. Over this season I will take a deep dive into each novel over a four part series. The four novels we will consider from the ethics and compliance perspective are A Study in Scarlet, The Sign of Four, The Hound of the Baskervilles and The Valley of Fear. We continue our four episode series on the second novel, The Sign of Four by reviewing how Holmes uses data analytics and pattern recognition in this story.
Timothy and Fiona had so much fun last week, they are back to explore how the methods of the fictional detective Sherlock Holmes can be applied to modern compliance work. By examining the principles from ‘The Sign of Four’, they take a deep dive into five key lessons that can sharpen the skills of compliance professionals today: the art of discernment, establishing baselines, contextual analysis of data, leveraging technology, and continuous refinement and learning. Their discussion highlights how these timeless analytical approaches, when amplified by modern technology, provide a robust framework for dealing with complex and rapidly changing compliance landscapes.
Highlights Include:
• Applying Holmes’ Methods to Compliance Analytics
• Lesson 1: The Art of Discernment
• Lesson 2: Establishing Baselines
• Lesson 3: Contextual Analysis of Data
• Lesson 4: Leveraging Technology and Tools
• Lesson 5: Continuous Refinement and Learning
• Conclusion: Balancing Timeless Principles with Modern Adaptability See less -
